Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Early identification of postpartum depression using demographic, clinical, and digital phenotyping

11 Feb 2021

Abstract excerpt

Postpartum depression (PPD) and adjustment disorder (AD) affect up to 25% of women after childbirth. However, there are no accurate screening tools for either disorder to identify at-risk mothers and enable them to benefit from early intervention. Combinations of anamnestic, clinical, and remote assessments were evaluated for an early and accurate identification of PPD and AD. Two cohorts of mothers giving birth...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Maternal Mental Health During Pregnancy and Postpartum

Source

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Identifiers

PMID: 33574229
DOI: 10.1038/s41398-021-01245-6

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Early identification of postpartum depression using demographic, clinical, and digital phenotypingPMID 33574229Read ↗

Stratifying Risk for Postpartum Depression at Time of Hospital DischargeSemantic proximity Read ↗

Predictors of Postpartum Depression: A Comprehensive Review of the Last Decade of Evidence.Semantic proximity Read ↗

Life-course comorbidity patterns and integrated prediction of postpartum depression, multimorbidity, and symptom progressionSemantic proximity Read ↗

Machine learning-optimized perinatal depression screening: Maximum impact, minimal burdenSemantic proximity Read ↗

Development of multivariable models to predict perinatal depression before and after delivery using patient reported survey responses at weeks 4-10 of pregnancySemantic proximity Read ↗

Pilot validation of blood-based biomarkers during pregnancy and postpartum in women with prior or current depressionSemantic proximity Read ↗

Digital phenotyping of depression during pregnancy using self-report data.Semantic proximity Read ↗

Examining the Distinctions and Features of Anxiety and Depression in Patients with Early Postpartum Stress Urinary IncontinenceSemantic proximity Read ↗

Clinical phenotypes of perinatal depression and time of symptom onset: analysis of data from an international consortium.Semantic proximity Read ↗

The PMADS Project: A Longitudinal Multimodal Cohort Study to Understand Risk for Perinatal Mood and Anxiety DisordersSemantic proximity Read ↗

Early predictive biomarkers for postpartum depression point to a role for estrogen receptor signalingSemantic proximity Read ↗

Toward personalized classification and treatment in depression: A narrative review of digital phenotyping and artificial intelligence.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.